Dense Neural Network Classification Model for Software Defined Network for Fine Grained Traffic Routing and Flow Analysis by Dr. Khaliq Ahmed, Maheen Danish, Asif Raza

“…Fine-grained traffic classification cannot be underestimated in SDN, given the wide gamut that runs applications over SDN networks. The DDNN model handles diverse types of traffic with a lot of efficiency through extracting deep features from complex datasets, hence increasing the capability of SDN to meet the ever-evolving demands in networks. …”
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A Method for Fault Localization in Distribution Networks with High Proportions of Distributed Generation Based on Graph Convolutional Networks by Xiping Ma, Wenxi Zhen, Haodong Ren, Guangru Zhang, Kai Zhang, Haiying Dong

“…By abstracting busbars and lines into graph structure nodes and edges, GCN captures spatial coupling relationships between nodes, using key electrical quantities such as node voltage magnitude, current magnitude, power, and phase angle as input features to construct a fault localization model. A multi-type fault dataset is generated using the Matpower toolbox, and model training is evaluated using K-fold cross-validation. …”
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MEFSR-GAN: A Multi-Exposure Feedback and Super-Resolution Multitask Network via Generative Adversarial Networks by Sibo Yu, Kun Wu, Guang Zhang, Wanhong Yan, Xiaodong Wang, Chen Tao

“…MEFSR-GAN includes a generator and two discriminators. The generator network consists of two parallel sub-networks for under-exposure and over-exposure, each containing a feature extraction block (FEB), a super-resolution block (SRB), and several multiple-exposure feedback blocks (MEFBs). …”
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Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis by Zhendong Sha, Philip J. Freda, Priyanka Bhandary, Attri Ghosh, Nicholas Matsumoto, Jason H. Moore, Ting Hu

“…Additionally, the XOR network features triangle network motifs, indicative of higher-order epistatic interactions. …”
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Distinguishable IQ Feature Representation for Domain-Adaptation Learning of WiFi Device Fingerprints by Abdurrahman Elmaghbub, Bechir Hamdaoui

“…By accurately capturing device hardware impairments while suppressing irrelevant domain information, <monospace>EPS</monospace> offers improved feature selection for DL models in RFFP. Our experimental evaluation demonstrates the effectiveness of the integration of <monospace>EPS</monospace> representation with a Convolution Neural Network (CNN) model, termed <monospace>EPS-CNN</monospace>, achieving over 99% testing accuracy in same-day/channel/location evaluations and 93% accuracy in cross-day evaluations, outperforming the traditional IQ representation. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The proposed GAT model showcases its effectiveness and promises results for addressing the OPF problem in the distribution network, as evidenced by performance evaluation metrics.…”
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A Comparative Analysis of Artificial Intelligence Techniques for Single Open-Circuit Fault Detection in a Packed E-Cell Inverter by Bushra Masri, Hiba Al Sheikh, Nabil Karami, Hadi Y. Kanaan, Nazih Moubayed

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Diagnosis of array antennas based on near-field data using Faster R-CNN by Boguang Yang, Yulun Wei, Jixiang Shi, Tao Hong, Liangyu Li, Kai-Da Xu

“…Four different excitation states are trained using the same neural network to compare the effects of excitation faults on feature extraction and classification accuracy. …”
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Perceptual Quality Assessment for Pansharpened Images Based on Deep Feature Similarity Measure by Zhenhua Zhang, Shenfu Zhang, Xiangchao Meng, Liang Chen, Feng Shao

“…Therefore, this paper proposes a perceptual quality assessment method based on deep feature similarity measure. The proposed network includes spatial/spectral feature extraction and similarity measure (FESM) branch and overall evaluation network. …”
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Evaluation of large‐scale cycling environment by using the trajectory data of dockless shared bicycles: A data‐driven approach by Ying Ni, Shihan Wang, Jiaqi Chen, Bufan Feng, Rongjie Yu, Yilin Cai

“…Assessing these environments is crucial, but existing methods face data challenges for large urban networks. This study proposes a data‐driven framework using dockless shared bicycle data to efficiently evaluate large‐scale cycling environments. …”
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An efficient parallel runoff forecasting model for capturing global and local feature information by Yang-hao Hong, Dong-mei Xu, Wen-chuan Wang, Hong-fei Zang, Xiao-xue Hu, Yan-wei Zhao

“…Additionally, due to the opacity in feature distribution processes of AI models, SHAP (Shapley Additive exPlanations) analysis was used to evaluate the contribution of each feature variable to long-term runoff trends. …”
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Feature Constraints Map Generation Models Integrating Generative Adversarial and Diffusion Denoising by Chenxing Sun, Xixi Fan, Xiechun Lu, Laner Zhou, Junli Zhao, Yuxuan Dong, Zhanlong Chen

“…The accelerated evolution of remote sensing technology has intensified the demand for real-time tile map generation, highlighting the limitations of conventional mapping approaches that rely on manual cartography and field surveys. …”
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Comparative Analysis of Hybrid Attention and Progressive Layering Through a Comprehensive Evaluation of ARU-Net and PLU-Net in Brain Tumour Segmentation by Noman Ahmed Siddiqui, Muhammad Tahir Qadri, Muhammad Ovais Akhter, Tahira Anwar, Fahad Farooq

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Underwater image enhancement using hybrid transformers and evolutionary particle swarm optimization by Ajay Kumar, Gagandeep Berar, Manmohan Sharma, Sakshi, Ajit Noonia, Gunjan Verma

“…The HTN-PSO framework combines the strengths of convolutional neural networks and transformer models to effectively capture low-level features and model long-range dependencies. …”
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Edge-YOLO: Lightweight Multi-Scale Feature Extraction for Industrial Surface Inspection by Wang Guiqiang, Chen Junbao, Li Chengzhang, Lu Shuo

“…The Edge-backbone systematically strengthens edge feature extraction and retention through three synergistic components: an Edge-Sensitive (EdgeS) module for optimized feature initialization, a Cross-Stage-Partial Edge Enhancement (C3E2) module that integrates edge information across network stages, and a Multi-Scale Dilated Convolution (MSDC) module that efficiently fuses multi-scale features through weight-sharing. …”
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Research on multi class pests identification and detection based on fusion attention mechanism with Mask-RCNN-CBAM by Xingwang Wang, Xingwang Wang, Xingwang Wang, Can Hu, Xufeng Wang, Hainie Zha, Xueyong Chen, Shanshan Yuan, Jing Zhang, Jianfeng Liao, Zhangying Ye

“…The framework combines three innovations: (1) a CBAM attention mechanism to amplify pest features while suppressing background noise; (2) a feature-enhanced pyramid network (FPN) for multi-scale feature fusion, enhancing small pest recognition; and (3) a dual-channel downsampling module to minimize detail loss during feature propagation. …”
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Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering by Jiang Luo, Lingjun Liu

“…The network makes the feature at the single‐part level also contain partial information of other body parts, making it more discriminative. …”
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Domain Alignment Dynamic Spectral and Spatial Feature Fusion for Hyperspectral Change Detection by Xuexiang Qin, Yuxiang Zhang, Yanni Dong

“…First, DADSSFF uses the main network to optimize the alignment of the mean (first-order statistics) and correlation (variance, second-order statistics) of the bitemporal images, coordinating features across both levels to alleviate the issue of inconsistent feature distribution. …”
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Fluvio-Karstic Development of the Masiro Canyon (Pervari) and Geomorphic Features of Its Surroundings by Halil Zorer, Yahya Öztürk

“…The Sinebel Creek valley network built on Neogene deposits was exposed to anticlinal uplift between Körkandil Mountain and Gülle Hill. …”
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Multimodal Fake News Detection Incorporating External Knowledge and User Interaction Feature by Lifang Fu, Shuai Liu

“…On the other hand, inspired by the “similarity effect” in social psychology, this paper constructs a user interaction network and defines the weighted GCN by calculating the feature similarity among users to analyze the mutual influence of users. …”
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